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Disorganized cortical thickness covariance network in major depressive disorder implicated by aberrant hubs in large-scale networks

Major depressive disorder is associated with abnormal anatomical and functional connectivity, yet alterations in whole cortical thickness topology remain unknown. Here, we examined cortical thickness in medication-free adult depression patients (n = 76) and matched healthy controls (n = 116). Inter-...

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Autores principales: Wang, Tao, Wang, Kangcheng, Qu, Hang, Zhou, Jingjing, Li, Qi, Deng, Zhou, Du, Xue, Lv, Fajin, Ren, Gaoping, Guo, Jing, Qiu, Jiang, Xie, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4908416/
https://www.ncbi.nlm.nih.gov/pubmed/27302485
http://dx.doi.org/10.1038/srep27964
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author Wang, Tao
Wang, Kangcheng
Qu, Hang
Zhou, Jingjing
Li, Qi
Deng, Zhou
Du, Xue
Lv, Fajin
Ren, Gaoping
Guo, Jing
Qiu, Jiang
Xie, Peng
author_facet Wang, Tao
Wang, Kangcheng
Qu, Hang
Zhou, Jingjing
Li, Qi
Deng, Zhou
Du, Xue
Lv, Fajin
Ren, Gaoping
Guo, Jing
Qiu, Jiang
Xie, Peng
author_sort Wang, Tao
collection PubMed
description Major depressive disorder is associated with abnormal anatomical and functional connectivity, yet alterations in whole cortical thickness topology remain unknown. Here, we examined cortical thickness in medication-free adult depression patients (n = 76) and matched healthy controls (n = 116). Inter-regional correlation was performed to construct brain networks. By applying graph theory analysis, global (i.e., small-worldness) and regional (centrality) topology was compared between major depressive disorder patients and healthy controls. We found that in depression patients, topological organization of the cortical thickness network shifted towards randomness, and lower small-worldness was driven by a decreased clustering coefficient. Consistently, altered nodal centrality was identified in the isthmus of the cingulate cortex, insula, supra-marginal gyrus, middle temporal gyrus and inferior parietal gyrus, all of which are components within the default mode, salience and central executive networks. Disrupted nodes anchored in the default mode and executive networks were associated with depression severity. The brain systems involved sustain core symptoms in depression and implicate a structural basis for depression. Our results highlight the possibility that developmental and genetic factors are crucial to understand the neuropathology of depression.
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spelling pubmed-49084162016-06-15 Disorganized cortical thickness covariance network in major depressive disorder implicated by aberrant hubs in large-scale networks Wang, Tao Wang, Kangcheng Qu, Hang Zhou, Jingjing Li, Qi Deng, Zhou Du, Xue Lv, Fajin Ren, Gaoping Guo, Jing Qiu, Jiang Xie, Peng Sci Rep Article Major depressive disorder is associated with abnormal anatomical and functional connectivity, yet alterations in whole cortical thickness topology remain unknown. Here, we examined cortical thickness in medication-free adult depression patients (n = 76) and matched healthy controls (n = 116). Inter-regional correlation was performed to construct brain networks. By applying graph theory analysis, global (i.e., small-worldness) and regional (centrality) topology was compared between major depressive disorder patients and healthy controls. We found that in depression patients, topological organization of the cortical thickness network shifted towards randomness, and lower small-worldness was driven by a decreased clustering coefficient. Consistently, altered nodal centrality was identified in the isthmus of the cingulate cortex, insula, supra-marginal gyrus, middle temporal gyrus and inferior parietal gyrus, all of which are components within the default mode, salience and central executive networks. Disrupted nodes anchored in the default mode and executive networks were associated with depression severity. The brain systems involved sustain core symptoms in depression and implicate a structural basis for depression. Our results highlight the possibility that developmental and genetic factors are crucial to understand the neuropathology of depression. Nature Publishing Group 2016-06-15 /pmc/articles/PMC4908416/ /pubmed/27302485 http://dx.doi.org/10.1038/srep27964 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Wang, Tao
Wang, Kangcheng
Qu, Hang
Zhou, Jingjing
Li, Qi
Deng, Zhou
Du, Xue
Lv, Fajin
Ren, Gaoping
Guo, Jing
Qiu, Jiang
Xie, Peng
Disorganized cortical thickness covariance network in major depressive disorder implicated by aberrant hubs in large-scale networks
title Disorganized cortical thickness covariance network in major depressive disorder implicated by aberrant hubs in large-scale networks
title_full Disorganized cortical thickness covariance network in major depressive disorder implicated by aberrant hubs in large-scale networks
title_fullStr Disorganized cortical thickness covariance network in major depressive disorder implicated by aberrant hubs in large-scale networks
title_full_unstemmed Disorganized cortical thickness covariance network in major depressive disorder implicated by aberrant hubs in large-scale networks
title_short Disorganized cortical thickness covariance network in major depressive disorder implicated by aberrant hubs in large-scale networks
title_sort disorganized cortical thickness covariance network in major depressive disorder implicated by aberrant hubs in large-scale networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4908416/
https://www.ncbi.nlm.nih.gov/pubmed/27302485
http://dx.doi.org/10.1038/srep27964
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